Trade-offs between Risk and Operational Cost in SDN Failure Recovery Plan

Saeed A. Astaneh, Shahram Shah Heydari (), Sara Taghavi Motlagh and Alireza Izaddoost
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Saeed A. Astaneh: Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON L1G 0C5, Canada
Shahram Shah Heydari: Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON L1G 0C5, Canada
Sara Taghavi Motlagh: Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON L1G 0C5, Canada
Alireza Izaddoost: Department of Computer Science, California State University, Dominguez Hills, Carson, CA 90747, USA

Future Internet, 2022, vol. 14, issue 9, 1-15

Abstract: We consider the problem of SDN flow optimization in the presence of a dynamic probabilistic link failures model. We introduce a metric for path risk, which can change dynamically as network conditions and failure probabilities change. As these probabilities change, the end-to-end path survivability probability may drop, i.e., its risk may rise. The main objective is to reroute at-risk end-to-end flows with the minimum number of flow operation so that a fast flow recovery is guaranteed. We provide various formulations for optimizing network risk versus operational costs and examine the trade-offs in flow recovery and the connections between operational cost, path risk, and path survival probability. We present our suboptimal dynamic flow restoration methods and evaluate their effectiveness against the Lagrangian relaxation approach. Our results show a significant improvement in operational cost against a shortest-path approach.

Keywords: network optimization; network probabilistic failures; software-defined networks; Lagrangian relaxation method (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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